{
  "nbformat_minor": 0, 
  "nbformat": 4, 
  "cells": [
    {
      "execution_count": null, 
      "cell_type": "code", 
      "source": [
        "%matplotlib inline"
      ], 
      "outputs": [], 
      "metadata": {
        "collapsed": false
      }
    }, 
    {
      "source": [
        "\n# Remap MEG channel types\n\n\nIn this example, MEG data are remapped from one\nchannel type to another. This is useful to:\n\n    - visualize combined magnetometers and gradiometers as magnetometers\n      or gradiometers.\n    - run statistics from both magnetometers and gradiometers while\n      working with a single type of channels.\n\n"
      ], 
      "cell_type": "markdown", 
      "metadata": {}
    }, 
    {
      "execution_count": null, 
      "cell_type": "code", 
      "source": [
        "# Author: Mainak Jas <mainak.jas@telecom-paristech.fr>\n\n# License: BSD (3-clause)\n\nimport mne\nfrom mne.datasets import sample\n\nprint(__doc__)\n\n# read the evoked\ndata_path = sample.data_path()\nfname = data_path + '/MEG/sample/sample_audvis-ave.fif'\nevoked = mne.read_evokeds(fname, condition='Left Auditory', baseline=(None, 0))\n\n# go from grad + mag to mag\nvirt_evoked = evoked.as_type('mag')\nevoked.plot_topomap(ch_type='mag', title='mag (original)')\nvirt_evoked.plot_topomap(ch_type='mag',\n                         title='mag (interpolated from mag + grad)')\n\n# go from grad + mag to grad\nvirt_evoked = evoked.as_type('grad')\nevoked.plot_topomap(ch_type='grad', title='grad (original)')\nvirt_evoked.plot_topomap(ch_type='grad',\n                         title='grad (interpolated from mag + grad)')"
      ], 
      "outputs": [], 
      "metadata": {
        "collapsed": false
      }
    }
  ], 
  "metadata": {
    "kernelspec": {
      "display_name": "Python 2", 
      "name": "python2", 
      "language": "python"
    }, 
    "language_info": {
      "mimetype": "text/x-python", 
      "nbconvert_exporter": "python", 
      "name": "python", 
      "file_extension": ".py", 
      "version": "2.7.13", 
      "pygments_lexer": "ipython2", 
      "codemirror_mode": {
        "version": 2, 
        "name": "ipython"
      }
    }
  }
}